title: Impact of delays on the synchronization transitions of modular neuronal networks with hybrid synapses.
abstract: The combined effects of the information transmission delay and the ratio of the electrical and chemical synapses on the synchronization transitions in the hybrid modular neuronal network are investigated in this paper. Numerical results show that the synchronization of neuron activities can be either promoted or destroyed as the information transmission delay increases, irrespective of the probability of electrical synapses in the hybrid-synaptic network. Interestingly, when the number of the electrical synapses exceeds a certain level, further increasing its proportion can obviously enhance the spatiotemporal synchronization transitions. Moreover, the coupling strength has a significant effect on the synchronization transition. The dominated type of the synapse always has a more profound effect on the emergency of the synchronous behaviors. Furthermore, the results of the modular neuronal network structures demonstrate that excessive partitioning of the modular network may result in the dramatic detriment of neuronal synchronization. Considering that information transmission delays are inevitable in intra- and inter-neuronal networks communication, the obtained results may have important implications for the exploration of the synchronization mechanism underlying several neural system diseases such as Parkinson's Disease.
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, People's Republic of China.
authors.forename: Chen
authors.initials: C
authors.lastname: Liu
authors.forename: Jiang
authors.initials: J
authors.lastname: Wang
authors.forename: Haitao
authors.initials: H
authors.lastname: Yu
authors.forename: Bin
authors.initials: B
authors.lastname: Deng
authors.forename: Xile
authors.initials: X
authors.lastname: Wei
authors.forename: Kaiming
authors.initials: K
authors.lastname: Tsang
authors.forename: Wailok
authors.initials: W
authors.lastname: Chan
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology; D006801:Humans; D008564:Membrane Potentials; D008954:Models, Biological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000166:cytology* / Q000473:pathology / Q000502:physiology; D017711:Nonlinear Dynamics; D010300:Parkinson Disease / Q000503:physiopathology; D013569:Synapses / Q000378:metabolism; D009435:Synaptic Transmission; D013696:Temperature; D013997:Time Factors